260 citations · 321 across the 45 of their papers we have counts for
4 papers · 1 filter
Neural Disparity Refinement for Arbitrary Resolution Stereo
Filippo Aleotti, Fabio Tosi, Pierluigi Zama Ramirez +4
We introduce a novel architecture for neural disparity refinement aimed at facilitating deployment of 3D computer vision on cheap and widespread consumer devices, such as mobile ph…
Sensor-Guided Optical Flow
Matteo Poggi, Filippo Aleotti, Stefano Mattoccia
This paper proposes a framework to guide an optical flow network with external cues to achieve superior accuracy either on known or unseen domains. Given the availability of sparse…
Learning optical flow from still images
Filippo Aleotti, Matteo Poggi, Stefano Mattoccia
This paper deals with the scarcity of data for training optical flow networks, highlighting the limitations of existing sources such as labeled synthetic datasets or unlabeled real…
On the confidence of stereo matching in a deep-learning era: a quantitative evaluation
Matteo Poggi, Seungryong Kim, Fabio Tosi +5
Stereo matching is one of the most popular techniques to estimate dense depth maps by finding the disparity between matching pixels on two, synchronized and rectified images. Along…